• Title/Summary/Keyword: Body Gesture Recognition

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The Effect of Visual Feedback on One-hand Gesture Performance in Vision-based Gesture Recognition System

  • Kim, Jun-Ho;Lim, Ji-Hyoun;Moon, Sung-Hyun
    • Journal of the Ergonomics Society of Korea
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    • v.31 no.4
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    • pp.551-556
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    • 2012
  • Objective: This study presents the effect of visual feedback on one-hand gesture performance in vision-based gesture recognition system when people use gestures to control a screen device remotely. Backgroud: gesture interaction receives growing attention because it uses advanced sensor technology and it allows users natural interaction using their own body motion. In generating motion, visual feedback has been to considered critical factor affect speed and accuracy. Method: three types of visual feedback(arrow, star, and animation) were selected and 20 gestures were listed. 12 participants perform each 20 gestures while given 3 types of visual feedback in turn. Results: People made longer hand trace and take longer time to make a gesture when they were given arrow shape feedback than star-shape feedback. The animation type feedback was most preferred. Conclusion: The type of visual feedback showed statistically significant effect on the length of hand trace, elapsed time, and speed of motion in performing a gesture. Application: This study could be applied to any device that needs visual feedback for device control. A big feedback generate shorter length of motion trace, less time, faster than smaller one when people performs gestures to control a device. So the big size of visual feedback would be recommended for a situation requiring fast actions. On the other hand, the smaller visual feedback would be recommended for a situation requiring elaborated actions.

Implementation of User Gesture Recognition System for manipulating a Floating Hologram Character (플로팅 홀로그램 캐릭터 조작을 위한 사용자 제스처 인식 시스템 구현)

  • Jang, Myeong-Soo;Lee, Woo-Beom
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.2
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    • pp.143-149
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    • 2019
  • Floating holograms are technologies that provide rich 3D stereoscopic images in a wide space such as advertisement, concert. In addition, It is possible to reduce the 3D glasses inconvenience, eye strain, and space distortion, and to enjoy 3D images with excellent realism and existence. Therefore, this paper implements a user gesture recognition system for manipulating a floating hologram characters that can be used in a small space devices. The proposed method detects face region using haar feature-based cascade classifier, and recognizes the user gestures using a user gesture-occurred position information that is acquired from the gesture difference image in real time. And Each classified gesture information is mapped to the character motion in floating hologram for manipulating a character action. In order to evaluate the performance of the proposed user gesture recognition system for manipulating a floating hologram character, we make the floating hologram display devise, and measures the recognition rate of each gesture repeatedly that includes body shaking, walking, hand shaking, and jumping. As a results, the average recognition rate was 88%.

HMM-based Upper-body Gesture Recognition for Virtual Playing Ground Interface (가상 놀이 공간 인터페이스를 위한 HMM 기반 상반신 제스처 인식)

  • Park, Jae-Wan;Oh, Chi-Min;Lee, Chil-Woo
    • The Journal of the Korea Contents Association
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    • v.10 no.8
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    • pp.11-17
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    • 2010
  • In this paper, we propose HMM-based upper-body gesture. First, to recognize gesture of space, division about pose that is composing gesture once should be put priority. In order to divide poses which using interface, we used two IR cameras established on front side and side. So we can divide and acquire in front side pose and side pose about one pose in each IR camera. We divided the acquired IR pose image using SVM's non-linear RBF kernel function. If we use RBF kernel, we can divide misclassification between non-linear classification poses. Like this, sequences of divided poses is recognized by gesture using HMM's state transition matrix. The recognized gesture can apply to existent application to do mapping to OS Value.

Recognition-Based Gesture Spotting for Video Game Interface (비디오 게임 인터페이스를 위한 인식 기반 제스처 분할)

  • Han, Eun-Jung;Kang, Hyun;Jung, Kee-Chul
    • Journal of Korea Multimedia Society
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    • v.8 no.9
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    • pp.1177-1186
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    • 2005
  • In vision-based interfaces for video games, gestures are used as commands of the games instead of pressing down a keyboard or a mouse. In these Interfaces, unintentional movements and continuous gestures have to be permitted to give a user more natural interface. For this problem, this paper proposes a novel gesture spotting method that combines spotting with recognition. It recognizes the meaningful movements concurrently while separating unintentional movements from a given image sequence. We applied our method to the recognition of the upper-body gestures for interfacing between a video game (Quake II) and its user. Experimental results show that the proposed method is on average $93.36\%$ in spotting gestures from continuous gestures, confirming its potential for a gesture-based interface for computer games.

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Interface of Interactive Contents using Vision-based Body Gesture Recognition (비전 기반 신체 제스처 인식을 이용한 상호작용 콘텐츠 인터페이스)

  • Park, Jae Wan;Song, Dae Hyun;Lee, Chil Woo
    • Smart Media Journal
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    • v.1 no.2
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    • pp.40-46
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    • 2012
  • In this paper, we describe interactive contents which is used the result of the inputted interface recognizing vision-based body gesture. Because the content uses the imp which is the common culture as the subject in Asia, we can enjoy it with culture familiarity. And also since the player can use their own gesture to fight with the imp in the game, they are naturally absorbed in the game. And the users can choose the multiple endings of the contents in the end of the scenario. In the part of the gesture recognition, KINECT is used to obtain the three-dimensional coordinates of each joint of the limb to capture the static pose of the actions. The vision-based 3D human pose recognition technology is used to method for convey human gesture in HCI(Human-Computer Interaction). 2D pose model based recognition method recognizes simple 2D human pose in particular environment On the other hand, 3D pose model which describes 3D human body skeletal structure can recognize more complex 3D pose than 2D pose model in because it can use joint angle and shape information of body part Because gestures can be presented through sequential static poses, we recognize the gestures which are configured poses by using HMM In this paper, we describe the interactive content which is used as input interface by using gesture recognition result. So, we can control the contents using only user's gestures naturally. And we intended to improve the immersion and the interest by using the imp who is used real-time interaction with user.

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Depth Image Poselets via Body Part-based Pose and Gesture Recognition (신체 부분 포즈를 이용한 깊이 영상 포즈렛과 제스처 인식)

  • Park, Jae Wan;Lee, Chil Woo
    • Smart Media Journal
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    • v.5 no.2
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    • pp.15-23
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    • 2016
  • In this paper we propose the depth-poselets using body-part-poses and also propose the method to recognize the gesture. Since the gestures are composed of sequential poses, in order to recognize a gesture, it should emphasize to obtain the time series pose. Because of distortion and high degree of freedom, it is difficult to recognize pose correctly. So, in this paper we used partial pose for obtaining a feature of the pose correctly without full-body-pose. In this paper, we define the 16 gestures, a depth image using a learning image was generated based on the defined gestures. The depth poselets that were proposed in this paper consists of principal three-dimensional coordinates of the depth image and its depth image of the body part. In the training process after receiving the input defined gesture by using a depth camera in order to train the gesture, the depth poselets were generated by obtaining 3D joint coordinates. And part-gesture HMM were constructed using the depth poselets. In the testing process after receiving the input test image by using a depth camera in order to test, it extracts foreground and extracts the body part of the input image by comparing depth poselets. And we check part gestures for recognizing gesture by using result of applying HMM. We can recognize the gestures efficiently by using HMM, and the recognition rates could be confirmed about 89%.

Kinect-based Motion Recognition Model for the 3D Contents Control (3D 콘텐츠 제어를 위한 키넥트 기반의 동작 인식 모델)

  • Choi, Han Suk
    • The Journal of the Korea Contents Association
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    • v.14 no.1
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    • pp.24-29
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    • 2014
  • This paper proposes a kinect-based human motion recognition model for the 3D contents control after tracking the human body gesture through the camera in the infrared kinect project. The proposed human motion model in this paper computes the distance variation of the body movement from shoulder to right and left hand, wrist, arm, and elbow. The human motion model is classified into the movement directions such as the left movement, right movement, up, down, enlargement, downsizing. and selection. The proposed kinect-based human motion recognition model is very natural and low cost compared to other contact type gesture recognition technologies and device based gesture technologies with the expensive hardware system.

A Framework for 3D Hand Gesture Design and Modeling (삼차원 핸드 제스쳐 디자인 및 모델링 프레임워크)

  • Kwon, Doo-Young
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.10
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    • pp.5169-5175
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    • 2013
  • We present a framework for 3D hand gesture design and modeling. We adapted two different pattern matching techniques, Dynamic Time Warping (DTW) and Hidden Markov Models (HMMs), to support the registration and evaluation of 3D hand gestures as well as their recognition. One key ingredient of our framework is a concept for the convenient gesture design and registration using HMMs. DTW is used to recognize hand gestures with a limited training data, and evaluate how the performed gesture is similar to its template gesture. We facilitate the use of visual sensors and body sensors for capturing both locative and inertial gesture information. In our experimental evaluation, we designed 18 example hand gestures and analyzed the performance of recognition methods and gesture features under various conditions. We discuss the variability between users in gesture performance.

Full-body Skeleton-based Motion Game System with Interactive Gesture Registration (상호작용적 제스처 등록이 가능한 전신 스켈레톤 기반 동작 게임 시스템)

  • Kim, Daehwan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.419-420
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    • 2022
  • This paper presents a method that allows users to interactively register their own gestures for a motion-based game system. Existing motion-based game systems create recognizers by collecting predefined gesture data. However, this sometimes requires difficult expertise or rather difficult courses. To alleviate these complex situations, we propose a full-body skeleton-based game system that can interactively register gestures.

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Gesture Recognition using Global and Partial Feature Information (전역 및 부분 특징 정보를 이용한 제스처 인식)

  • Lee, Yong-Jae;Lee, Chil-Woo
    • Journal of KIISE:Software and Applications
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    • v.32 no.8
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    • pp.759-768
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    • 2005
  • This paper describes an algorithm that can recognize gestures constructing subspace gesture symbols with hybrid feature information. The previous popular methods based on geometric feature and appearance have resulted in ambiguous output in case of recognizing between similar gesture because they use just the Position information of the hands, feet or bodily shape features. However, our proposed method can classify not only recognition of motion but also similar gestures by the partial feature information presenting which parts of body move and the global feature information including 2-dimensional bodily motion. And this method which is a simple and robust recognition algorithm can be applied in various application such surveillance system and intelligent interface systems.